Rules along with their exceptions are generally used for explaining a large dataset associated with a survey conducted in a particular domain. Since the rules (i.e., rules set) are huge in content, identifying interesting rules amongst the rules set becomes a challenge. Due to the huge content of the rules set, multiple overlapping patterns are created which is not easy to comprehend. For comprehending the rules (rules set) and exceptions in a perceptually effective manner and communicating these to end-users, visualization of the rules and exceptions is required.
In general, the rules are implication of the form X→Y, wherein X is an antecedent and Y is consequent. In one of a known visualization technique, the antecedents of the rules set are plotted against consequents in one-to-one and many-to-one relationship (i.e., A→C, B→C, and A+B→C). The one-to-one and many-to-one mappings are visualized in the form of a matrix. Unfortunately, when the number of antecedents and consequents increases in the given rules set, the visualization of antecedent-to-consequent mapping on the visualization becomes unwieldy and difficult to understand for end-users.
Further, the one-to-one and the many-to-one mappings may also be shown in a three-dimensional (3D) landscape. In the 3D landscape, more important rules are placed in foreground and less important rules are placed in background. Further, each rule of the rules set is shown as a sphere whose area represents support, and a cone whose height represents confidence. However, the use of 3D representation for visualizing the rules set creates another issue of occlusion. The occlusion results in hiding of data points on the 3D interface when seen at a certain viewing angle. Also, the 3D interface becomes quite complex and is harder to understand/learn for the end-users. Further, perspective projection also distorts sizes of the objects of the 3D interface. Thus, in the above discussed visualization techniques, a common issue of perceptually visualizing the huge content of the rules set is lacking.